<html><head><title>Statistician - Oakland, CA 94612</title></head>
<body><h2>Statistician - Oakland, CA 94612</h2>
<div><div><p><b>Position Description</b>:<br/>
</p><p>
Mathematica is a nationally recognized, nonpartisan research organization that conducts social policy research on health care, disability, education, welfare, nutrition, and other topics. Our mission is to improve public well-being by bringing the highest standards of quality, objectivity, and excellence to bear on the work we do for our clients, which include federal, state, and local government agencies, as well as private foundations. Mathematica’s workforce of more than 1200 social scientists, data analytics professionals, support staff and administrators is committed to providing the policymaking community with the evidence to build better social programs. We offer our employees a stimulating team-oriented work environment, competitive salaries, and a comprehensive benefits package, as well as the advantages of employee ownership.</p><p>
We are looking for PhD-level statisticians to join our vibrant group of over 50 statisticians and data scientists. The contributions of our statisticians underpin our ability to produce crucial evidence and information for policy and decision makers. We provide support for staff to engage in professional activities such as journal publications and conference participation.</p><p>
Position Responsibilities:</p><ul><li><b>
Analysis.</b> Apply a wide array of statistical methods to evaluate social programs and policies, by designing rigorous studies, conducting analyses, visualizing results, interpreting findings, drafting reports, and presenting inferences to policymakers and other stakeholders</li><li><b>
Methods development.</b> Leverage deep technical expertise in statistical methodology to improve upon existing analytic methods for policy research</li><li><b>
Mentorship.</b> Oversee the analyses of junior statisticians and data scientists, and support their professional development</li><li><b>
Business development.</b> Author the quantitative methods sections of proposals for new research projects</li><li><b>
Teamwork.</b> Participate actively and thoughtfully in multidisciplinary teams</li></ul></div><p></p><div><p><b>
Position Requirements</b>:<br/>
</p><ul><li>Doctoral degree in a quantitative discipline, such as statistics, biostatistics, applied mathematics, or a related field</li><li>Expertise in statistical methods such as program evaluation, experimental design, natural language processing, Bayesian inference, hierarchical/multilevel modeling, longitudinal data analysis, quality measurement, and/or predictive modeling</li><li>Fluency in one or more of the following statistical programming languages: R, Python, Stan, SAS, Stata, and/or Julia</li><li>Excellent written and oral communication skills, including an ability to translate statistical methods and findings for a non-technical audience</li><li>Experience contributing to proposals preferred</li><li>Subject-matter knowledge in the health policy field preferred</li></ul><p>
To apply, please submit a cover letter, resume, writing sample, and coding sample at the time of application. Review of applications will start in May 2019, applications completed before June 2019 will receive priority in consideration.</p><p>
Various federal agencies with whom we contract require that staff successfully undergo a background investigation or security clearance as a condition of working on the project. If you work on such a project, you will be required to obtain the requisite security clearance.</p><p>
Available Locations: Cambridge, MA; Washington, DC;<br/>
<br/>
Other locations (Princeton, NJ; Chicago, IL; Oakland, CA; Seattle, WA; Woodlawn, MD) will be considered.
</p></div></div><p></p><p>We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.</p></body>
</html>